Triple
T7672497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Buck |
E173780
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Buck |
E68722
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Buck | Statement: [Chris Buck, familyName, Buck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buck Context triple: [Chris Buck, familyName, Buck]
-
A.
Buck
chosen
Buck is a surname most prominently associated with American sportscaster Joe Buck, known for his play-by-play commentary on major baseball and football broadcasts.
-
B.
Buck
Buck is the nickname of Buck Weaver, an American third baseman best known as one of the Chicago White Sox players implicated in the 1919 Black Sox Scandal.
-
C.
Buck
Buck is a one-eyed, adventure-loving weasel who serves as a fearless and eccentric guide in the Ice Age animated film series.
-
D.
Buck
Buck was the nickname of Earl Van Dorn, a Confederate major general in the American Civil War known for his aggressive cavalry operations.
-
E.
Buck
Buck is the central outlaw character in the horror-crime film "From Dusk Till Dawn 2: Texas Blood Money," leading a gang into a deadly vampire-infested heist.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6995703e0819081de77361b602e78 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701de94208190a7627521211452dc |
completed | March 27, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a22f74f481909498391bfaf23428 |
completed | March 29, 2026, 3:53 a.m. |
Created at: March 27, 2026, 4 p.m.